Beginner
Installing FastAI
Get FastAI running on your machine in minutes. We cover pip and conda installation, GPU configuration, and cloud notebook options.
Install with pip
Bash
# Install fastai (includes PyTorch) pip install fastai # Or with specific PyTorch version pip install torch torchvision torchaudio pip install fastai
Install with conda
Bash
# Using conda (recommended for managing CUDA dependencies)
conda install -c fastchan fastai
Easiest Option: Use Google Colab or Kaggle Notebooks. FastAI comes pre-installed with GPU access - no setup required. Just open a notebook and start with
from fastai.vision.all import *.
GPU Setup
FastAI uses PyTorch's CUDA support. If you have an NVIDIA GPU:
Bash
# Verify CUDA is available python -c "import torch; print(torch.cuda.is_available())" # Check GPU details python -c "import torch; print(torch.cuda.get_device_name(0))"
Verify Your Installation
Python
from fastai.vision.all import * # Check version import fastai print(f"fastai version: {fastai.__version__}") # Quick test: download and train a model path = untar_data(URLs.PETS) print(f"Dataset downloaded to: {path}") print("FastAI is working!")
Cloud Notebook Options
| Platform | Free GPU | Setup Required |
|---|---|---|
| Google Colab | Yes (T4/V100) | None - fastai pre-installed |
| Kaggle Notebooks | Yes (P100/T4) | None - fastai pre-installed |
| Paperspace Gradient | Free tier available | Minimal - fastai template available |
| AWS SageMaker | No (paid) | Some setup required |
Next Up: Vision
Now that FastAI is installed, let's build your first image classifier with just a few lines of code.
Next: Vision →Ready to Go Deeper?
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